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Single-cell profiling guided combinatorial immunotherapy for breast cancer resistance to Her2/neu and CDK4/6 targeted therapy

ABSTRACT: Trastuzumab (Herceptin™), a humanized monoclonal antibody targeting the extracellular domain of human epidermal growth factor receptor-2 (HER2), is one of the most successful examples of targeted therapies for HER2-positive breast cancer. However, drug resistance remains daunting challenges. New combinatorial regimen of CDK4/6 inhibitors plus trastuzumab is currently under active clinical investigations. In this study, we seek to prospectively model the in vivo response to CDK4/6 inhibitor Palbociclib (Pal) plus trastuzumab (Ab) using transgenic Her2/Neu mouse model in parallel with the current clinical trial scenario. We performed single cell RNA-seqencing (Drop-seq) to profile and compare tumor cells and infiltrated immune cells derived from control, Ab+Pal sensitive/residual (APS) and resistant/progressive (APR) tumors. We revealed that although Ab+Pal treatment enhanced antigen processing, presentation and interferon signaling on tumor cells, a distinct immunosuppressive immature myeloid cells (IMCs) infiltrated in the resistant tumor microenvironment to promote resistant phenotype. Based on single cell gene set enrichment analysis (profiling) guided drug screening, we identified and evaluated a combinatorial immunotherapy regimen. We found that combinatorial immunotherapy with receptor tyrosine kinase inhibitor Cabozantinib and immune checkpoint blockades overcome Ab+Pal resistance by inhibiting IMCs and enhancing anti-tumor immunity. Moreover, our rationally designed sequential combinatorial regimens enabled durable response and sustained controlling of the emergence of acquired resistance, thus significantly improved outcomes of rapidly evolving Her2/Neu positive breast cancers. Our results implicate that single-cell RNA sequencing profiling guided combinatorial immunotherapy as a strategy to mitigate the emergence of resistance and to achieve long-term therapeutic benefit merits clinical translation.

ORGANISM(S): Mus musculus

PROVIDER: GSE122336 | GEO | 2019/06/19

REPOSITORIES: GEO

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Project description:Faratian2009 - Role of PTEN in Trastuzumab resistance This model is described in the article: Systems biology reveals new strategies for personalizing cancer medicine and confirms the role of PTEN in resistance to trastuzumab. Faratian D, Goltsov A, Lebedeva G, Sorokin A, Moodie S, Mullen P, Kay C, Um IH, Langdon S, Goryanin I, Harrison DJ. Cancer Res. 2009 Aug; 69(16): 6713-6720 Abstract: Resistance to targeted cancer therapies such as trastuzumab is a frequent clinical problem not solely because of insufficient expression of HER2 receptor but also because of the overriding activation states of cell signaling pathways. Systems biology approaches lend themselves to rapid in silico testing of factors, which may confer resistance to targeted therapies. Inthis study, we aimed to develop a new kinetic model that could be interrogated to predict resistance to receptor tyrosine kinase (RTK) inhibitor therapies and directly test predictions in vitro and in clinical samples. The new mathematical model included RTK inhibitor antibody binding, HER2/HER3 dimerization and inhibition, AKT/mitogen-activated protein kinase cross-talk, and the regulatory properties of PTEN. The model was parameterized using quantitative phosphoprotein expression data from cancer cell lines using reverse-phase protein microarrays. Quantitative PTEN protein expression was found to be the key determinant of resistance to anti-HER2 therapy in silico, which was predictive of unseen experiments in vitro using the PTEN inhibitor bp(V). When measured in cancer cell lines, PTEN expression predicts sensitivity to anti-HER2 therapy; furthermore, this quantitative measurement is more predictive of response (relative risk, 3.0; 95% confidence interval, 1.6-5.5; P < 0.0001) than other pathway components taken in isolation and when tested by multivariate analysis in a cohort of 122 breast cancers treated with trastuzumab. For the first time, a systems biology approach has successfully been used to stratify patients for personalized therapy in cancer and is further compelling evidence that PTEN, appropriately measured in the clinical setting, refines clinical decision making in patients treated with anti-HER2 therapies. This model is hosted on BioModels Database and identified by: BIOMD0000000424. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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Single-cell profiling guided combinatorial immunotherapy for breast cancer resistance to Her2/neu and CDK4/6 targeted therapy

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